| 基于MSD-ICA-EA的轴承故障诊断方法 |
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| 引用本文： | 柳守斌,朱颖,刘宗田. 基于MSD-ICA-EA的轴承故障诊断方法[J]. 轴承, 2008, 0(1): 33-36 |
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| 作者姓名： | 柳守斌 朱颖 刘宗田 |
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| 作者单位： | 上海大学,计算机工程与科学学院,上海,200072 |
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| 摘 要： | 轴承故障诊断时,传感器采集的故障声音信号一般含有多个故障源,且源信号之间统计相关,应用传统的独立分量分析受到限制,本文应用多分辨率子带分解的独立分量分析方法(MSD-ICA),针对小波变换快速独立分量分析分离出的高频子带信号常呈现调制特性,提出进一步结合包络分析(EA)方法分析该子带信号,来判定故障的类型与部位.试验表明,多分辨率子带分解的独立分量分析结合包络分析的分析方法能有效地解决该类问题.
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| 关 键 词： | 滚动轴承 故障诊断 声音信号 独立分量分析 小波变换 包络分析 轴承故障诊断 诊断方法 Based Fault Diagnosis Bearing 问题 试验 类型 包络分析 结合 调制特性 源信号 高频子带 分析分离 独立分量分析 快速 小波变换 子带分解 多分辨率 应用 |
| 文章编号： | 1000-3762(2008)01-0033-04 |
| 修稿时间： | 2007-09-24 |
Method for Bearing Fault Diagnosis Based on MSD-ICA-EA |
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| LIU Shou-bin,ZHU Ying,LIU Zong-tian. Method for Bearing Fault Diagnosis Based on MSD-ICA-EA[J]. Bearing, 2008, 0(1): 33-36 |
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| Authors: | LIU Shou-bin ZHU Ying LIU Zong-tian |
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| Abstract: | Bearing faults are caused by several reasons and the original fault source signals are statistically correlative each other in practical problem,conventional independent component analysis is restricted.A method,integration of multiresolution subband decomposition and independent component analysis,is proposed.High frequency subband signal with amplitude modulation,separated by wavelet transform and fast ICA,is further analyzed by envelope analysis to diagnose bearing faults.Experimental result shows that MSD-ICA-EA is effective to solve the problem. |
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| Keywords: | rolling bearing fault diagnosis acoustic signal independent component analysis wavelet transform envelope analysis |
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